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Update app.py
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app.py
CHANGED
@@ -14,18 +14,27 @@ def load_model():
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tokenizer, model = load_model()
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# Step
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def correct_spelling(text):
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spell = SpellChecker()
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words = re.findall(r'\b\w+\b|\S', text)
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corrected_words = []
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for word in words:
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# Remove non-alphanumeric characters for spellcheck
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clean_word = re.sub(r'[^\w\s]', '', word)
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if clean_word.isalpha():
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corrected_word = spell.correction(clean_word.lower()) or clean_word
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# Restore punctuation
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trailing = ''.join(re.findall(r'[^\w\s]', word))
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corrected_words.append(corrected_word + trailing)
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else:
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@@ -33,7 +42,7 @@ def correct_spelling(text):
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return ' '.join(corrected_words)
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# Step 2: Grammar
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def correct_grammar(text):
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input_text = "gec: " + text
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input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
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@@ -41,31 +50,38 @@ def correct_grammar(text):
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corrected = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return corrected
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# UI
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st.set_page_config(page_title="Grammar & Spelling Assistant", page_icon="π§ ")
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st.title("π§ Grammar & Spelling Correction Assistant")
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st.write("Fixes
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user_input = st.text_area("βοΈ Enter your sentence
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if st.button("Correct & Explain"):
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if not user_input.strip():
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st.warning("Please enter a sentence.")
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else:
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# Step
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# Step 2: Grammar correction
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final_output = correct_grammar(spelling_fixed)
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st.markdown("### β
Final Correction:")
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st.success(final_output)
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st.markdown("### π Explanation
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st.info(f"""
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**Original Sentence:**
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{user_input}
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**After Spelling Correction:**
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{spelling_fixed}
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@@ -73,7 +89,8 @@ if st.button("Correct & Explain"):
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{final_output}
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**Explanation:**
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""")
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tokenizer, model = load_model()
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# Step 0: Preprocess the input
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def preprocess_input(text):
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# Remove special characters like '#' from the end
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cleaned = re.sub(r'[^\w\s]$', '', text.strip())
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# Ensure sentence ends with a period if not already
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if not cleaned.endswith('.'):
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cleaned += '.'
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return cleaned
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# Step 1: Spelling correction
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def correct_spelling(text):
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spell = SpellChecker()
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words = re.findall(r'\b\w+\b|\S', text)
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corrected_words = []
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for word in words:
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clean_word = re.sub(r'[^\w\s]', '', word)
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if clean_word.isalpha():
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corrected_word = spell.correction(clean_word.lower()) or clean_word
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trailing = ''.join(re.findall(r'[^\w\s]', word))
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corrected_words.append(corrected_word + trailing)
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else:
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return ' '.join(corrected_words)
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# Step 2: Grammar correction
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def correct_grammar(text):
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input_text = "gec: " + text
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input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
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corrected = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return corrected
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# Streamlit UI
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st.set_page_config(page_title="Grammar & Spelling Assistant", page_icon="π§ ")
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st.title("π§ Grammar & Spelling Correction Assistant")
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st.write("Fixes grammar and spelling errors without changing your original meaning.")
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user_input = st.text_area("βοΈ Enter your sentence:", height=150)
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if st.button("Correct & Explain"):
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if not user_input.strip():
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st.warning("Please enter a sentence.")
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else:
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# Step 0: Preprocess
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preprocessed = preprocess_input(user_input)
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# Step 1: Spell check
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spelling_fixed = correct_spelling(preprocessed)
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# Step 2: Grammar correction
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final_output = correct_grammar(spelling_fixed)
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# Output
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st.markdown("### β
Final Correction:")
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st.success(final_output)
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st.markdown("### π Explanation:")
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st.info(f"""
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**Original Sentence:**
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{user_input}
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**After Preprocessing (remove #, enforce period):**
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{preprocessed}
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**After Spelling Correction:**
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{spelling_fixed}
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{final_output}
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**Explanation:**
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- Special characters like `#` were removed
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- Misspelled words like `ober` β `over`, `dogz` β `dogs` were fixed
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- Grammar (capitalization, punctuation) was corrected
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- No unwanted words like `#5` were added
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""")
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